Cardiovascular

Strokes

Latest AI and machine learning research in strokes for healthcare professionals.

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Robotic-assisted gait training in neurological patients: who may benefit?

Regaining one's ability to walk is of great importance for neurological patients and is a major goal...

Serum tests, liver stiffness and artificial neural networks for diagnosing cirrhosis and portal hypertension.

BACKGROUND: The diagnostic performance of biochemical scores and artificial neural network models fo...

PhenoMiner: a quantitative phenotype database for the laboratory rat, Rattus norvegicus. Application in hypertension and renal disease.

Rats have been used extensively as animal models to study physiological and pathological processes i...

A review of technological and clinical aspects of robot-aided rehabilitation of upper-extremity after stroke.

Cerebrovascular accident (CVA) or stroke is one of the leading causes of disability and loss of moto...

Wrist Rehabilitation Assisted by an Electromyography-Driven Neuromuscular Electrical Stimulation Robot After Stroke.

BACKGROUND: Augmented physical training with assistance from robot and neuromuscular electrical stim...

Robotic telepresence versus standardly supervised stroke alert team assessments.

BACKGROUND: Telemedicine has created access to emergency stroke care for patients in all communities...

How could robotic training and botolinum toxin be combined in chronic post stroke upper limb spasticity? A pilot study.

BACKGROUND: Spasticity has a role of primary importance in functional motor recovery of upper limb a...

Assist-as-Needed Robot-Aided Gait Training Improves Walking Function in Individuals Following Stroke.

A novel robot-aided assist-as-needed gait training paradigm has been developed recently. This paradi...

An assistive control approach for a lower-limb exoskeleton to facilitate recovery of walking following stroke.

This paper presents a control approach for a lower-limb exoskeleton intended to facilitate recovery ...

Identifying Neuroimaging Markers of Motor Disability in Acute Stroke by Machine Learning Techniques.

Conventional mass-univariate analyses have been previously used to test for group differences in neu...

A Randomized Controlled Trial of EEG-Based Motor Imagery Brain-Computer Interface Robotic Rehabilitation for Stroke.

Electroencephalography (EEG)-based motor imagery (MI) brain-computer interface (BCI) technology has ...

Stroke parameters identification algorithm in handwriting movements analysis by synthesis.

This paper presents a new approach to identify the stroke parameters in handwriting movement data un...

Recovery of walking ability using a robotic device in subacute stroke patients: a randomized controlled study.

PURPOSE: This study investigates the effectiveness of Lokomat + conventional therapy in recovering w...

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